Performance of LIDAR- and radar-based turbulence intensity measurement in comparison with anemometer-based turbulence intensity estimation based on aircraft data for a typical case of terrain-induced turbulence in association with a typhoon

The Hong Kong Observatory (HKO) provides low-level turbulence alerting service for the Hong Kong International Airport (HKIA) through the windshear and turbulence warning system (WTWS). In the WTWS, turbulence intensities along the flight paths of the airport are estimated based upon correlation equations established between the surface anemometer data and the turbulence data from research aircraft before the opening of the airport. The research aircraft data are not available on day-to-day basis. The remote sensing meteorological instruments, such as the Doppler light detection and ranging (LIDAR) and radar, may be used to provide direct measurements of turbulence intensities over the runway corridors. The performances of LIDAR- and radar-based turbulence intensity data are studied in this paper based on actual turbulence intensity measurements made on 423 commercial jets for a typical case of terrain-induced turbulence in association with a typhoon. It turns out that, with the tuning of the relative operating characteristic (ROC) curve between hit rate and false alarm rate, the LIDAR-based turbulence intensity measurement performs better than the anemometer-based estimation of WTWS for turbulence intensity at moderate level or above. On the other hand, the radar-based measurement does not perform as well when compared with WTWS. By combining LIDAR- and radar-based measurements, the performance is slightly better than WTWS, mainly as a result of contribution from LIDAR-based measurement. As a result, the LIDAR-based turbulence intensity measurement could be used to replace anemometer-based estimate for non-rainy weather conditions. Further enhancements of radar-based turbulence intensity measurement in rain would be necessary.     

教育专网:助力中国教育信息化迈上新台阶——访中国工程院院士吴建平教授

吴建平院士介绍了互联网的核心技术和中国教育科研网建设的历程。吴院士团队实现IPv6关键技术的突破,使得中国教育科研网走在了世界互联网建设的前列:CERNET已经成为全球最大的学术网络。“互联网+教育”应用也是吴院士重点关注的内容。结合当前互联网教育现状,吴院士从缩小数字鸿沟、推进教育公平、确保青少年健康成长等方面探讨了教育专网建设的必要性,并界定了教育专网建设的概念和内涵,分析了教育专网建设的基本框架和可能带来的教育管理上的变革。他提出,教育专网将提供快速、稳定、绿色、安全的教育服务,作为智慧教育的支撑平台,支撑各种新兴技术对教育的渗透,进而对教育资源建设、教育改革方面发挥积极作用。未来教育场景中,教育专网必将成为“教、学、管、评、测”全链条信息化、智慧化的基础平台,将推动我国教育高质量均衡发展。     

Estimating Latent Variable Interactions with the Unconstrained Approach: A Comparison of Methods to Form Product Indicators for Large,Unequal Numbers of Items

This Monte Carlo simulation study investigated methods of forming product indicators for the unconstrained approach for latent variable interaction estimation when the exogenous factors are measured by large and unequal numbers of indicators. Product indicators were created based on multiplying parcels of the larger scale by indicators of the smaller scale, multiplying the three most reliable indicators of each scale matched by reliability, and matching items by reliability to create as many product indicators as the number of indicators of the smallest scale. The unconstrained approach was compared with the latent moderated structural equations (LMS) approach. All methods considered provided unbiased parameter estimates. Unbiased standard errors were obtained in all conditions with the LMS approach and when the sample size was large with the unconstrained approach. Power levels to test the latent interaction and Type I error rates were similar for all methods but slightly better for the LMS approach.